The application of digital techniques to video signal processing has heretofore focused on the manipulation of a digital representation of the entire video signal. U.S. Pat. Nos. 3,707,598; 3,748,644; 3,943,277; and 4,133,004 represent examples of this approach.
Although the speed of digital hardware has increased dramatically over the past decade, real-time manipulation of digital video signals is nevertheless limited by the high information density encountered in video signals. As a result, present digital video systems typically lack flexibility or accuracy; require large areas of digital memory for storing whole input scenes; or depend on expensive high-speed digital components.
Using present teachings, the detection of points of light could be accomplished by comparing the digital video signal with the preset digital threshold, and counting the successive digital samples which meet the threshold to measure the duration of the video pulse. The deficiency manifest in such an implementation is that, unless an extremely high sampling frequency is used, accurate adjustment of the size and sharpness detection criteria for spots or points of light to be accepted is impossible. As a result of this particular shortcoming, digital processing has not been effectively applied to optical matched filters.
The theory of optical spatial filtering is well known. A discussion of the implementation of optical matched filters may be found, for example, in "Signal Detection by Complex Spatial Filtering," by A. Vander Lugt, IEEE Transactions on Information Theory, April 1964, pp 139-145.
An Automatic Target Recognition System is disclosed in U.S. Pat. No. 3,779,492, assigned to the present assignee, which utilizes optical spatial filtering techhnology. As described, the matched filter system of this patent represents a powerful tool which may be adapted to a number of environments where automatic optical recognition is needed. However, the correlation plane output by the system disclosed in U.S. Pat. No. 3,779,492 may include hundreds of correlation spots or relatively bright points or areas of light which would require a significant effort on the part of a trained operator to interpret. Each correlation spot will have a sharpness proportional to the closeness of the match between the known matched filter object and the input scene object from which it results, but the brightness of each correlation spot depends further on the brightness of the input scene object.
Thus, several factors make it difficult for the operator to recognize autocorrelation spots, representing matched objects. The cross-correlation spots resulting from nearly unmatched objects may overlap nearby auto-correlation spots. Since autocorrelation spots are very sharp points of light, they can, therefore, become "lost" in nearby cross-correlations. Also, a very bright unmatched object can result in a much brighter cross-correlation than the autocorrelation of a poorly illuminated matched object in the input scene.